"Higher order" addiction molecular genetics: Convergent data from genome-wide association in humans and mice

George R. Uhl, Tomas Drgon, Catherine Johnson, Oluwatosin O. Fatusin, Qing Rong Liu, Carlo Contoreggi, Chuan Yun Li, Kari Buck, John Crabbe

Research output: Contribution to journalArticlepeer-review

120 Scopus citations


Family, adoption and twin data each support substantial heritability for addictions. Most of this heritable influence is not substance-specific. The overlapping genetic vulnerability for developing dependence on a variety of addictive substances suggests large roles for "higher order" pharamacogenomics in addiction molecular genetics. We and others have now completed genome-wide association (GWA) studies of DNAs from individuals with dependence on a variety of addictive substances versus appropriate controls. Recently reported replicated GWA observations identify a number of genes based on comparisons between controls and European-American and African-American polysubstance abusers. Here we review the convergence between these results and data that compares control samples and (a) alcohol-dependent European-Americans, (b) methamphetamine-dependent Asians and (c) nicotine dependent samples from European backgrounds. We also compare these human data to quantitative trait locus (QTL) results from studies of addiction-related phenotypes in mice that focus on alcohol, methamphetamine and barbiturates. These comparisons support a genetic architecture built from largely polygenic contributions of common allelic variants to dependence on a variety of legal and illegal substances. Many of the gene variants identified in this way are likely to alter specification and maintenance of neuronal connections.

Original languageEnglish (US)
Pages (from-to)98-111
Number of pages14
JournalBiochemical Pharmacology
Issue number1
StatePublished - Jan 1 2008
Externally publishedYes


  • Association genome scanning
  • Microarray
  • Neuronal connections
  • Pooled
  • Substance dependence

ASJC Scopus subject areas

  • Biochemistry
  • Pharmacology


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